Search Results (8,541)

Winter wheat is a cornerstone of China’s grain production, contributing substantially to national food security and overall cereal output. This study modeled the nonlinear associations between multitemporal remote sensing variables and winter wheat yield. To produce high-spatiotemporal-resolution inputs, we used the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to integrate Sentinel-2 normalized difference vegetation index (NDVI) data with MODIS NDVI data, generating NDVI composites at 8-day intervals with a 10-m spatial resolution. The NDVI, actual evapotranspiration (ET), land surface temperature (LST), precipitation (PRE), and soil moisture (SM) were selected as predictors for yield estimation because they are closely associated with winter wheat growth and yield formation during primary growth stages. By integrating the local temporal feature-learning capacity of a one-dimensional convolutional neural network (1-D CNN) with the strength of a bidirectional long short-term memory (BiLSTM) model in capturing temporal dependencies within time series, a BiLSTM–CNN model was constructed for wheat yield estimation and prediction. The BiLSTM–CNN model showed higher estimation accuracy than individual BiLSTM and 1-D CNN models, with an R² of 0.69 and root mean square error (RMSE) of 478.68 kg/hm². The use of all the parameters produced the best estimation performance among all the parameter combinations. Approximately two months before harvest, the model still provided satisfactory yield prediction accuracy. This study provides an important theoretical basis for high-accuracy regional winter wheat yield estimation and pre-harvest forecasting. Full article

Understanding the acclimation responses of conifer species with different functional types in response to altitudinal gradient changes is of significance for deepening our knowledge of how plants cope with global climate change. This study focused on seedlings of larch (Larix principis-rupprechtii) and spruce (Picea meyeri) within the Pangquangou Nature Reserve in North-central China. By setting two seedling source altitudes (1600 m, 2400 m) and four transplant altitudes (1600 m, 1900 m, 2100 m, 2400 m), we compared the response characteristics of 20 functional traits, including light response, instantaneous photosynthesis, leaf morphology and nutrient storage. The results showed that: (1) Tree functional type was the core factor determining the altitudinal response pattern of seedlings. Larch exhibited higher sensitivity to altitude change, and its photosynthetic (Amax, AQE, LSP, E) and morphological strategy traits (PA, SL, SW, SLA) changed significantly with altitude. (2) The regulation of phenotypic plasticity by seedling source altitude showed a significant functional-type dependence. The larch was significantly regulated by seedling source altitude, with low-altitude seedling sources displaying higher plasticity in traits such as H:D ratio, Tr and NSC. The spruce showed smaller differences between seedling sources, yet exhibited stronger environmental dynamic plasticity than the larch in carbon storage and utilization strategies (Sugars, NSC). (3) The two tree species coped with altitudinal gradient changes through differentiated trait variation pathways. Larch was primarily driven by carbon metabolism and protein synthesis (C, Protein), which was manifested in adjustments of photosynthetic capacity (Pn) and morphology (leaves and branches), thereby achieving rapid adaptation. In spruce, functional traits such as Pn, SLA and NSC were highly coupled; regardless of seedling source, photosynthetic and leaf morphological traits served as the core drivers, and coordinated changes in multiple traits were relied upon to maintain physiological homeostasis. Full article

The climate crisis exacerbates structural inequalities and disproportionately affects women, particularly in rural and low-income contexts where limited access to resources, education and financing undermines their adaptive capacity. This article examines how gender considerations are integrated into European Union (EU) climate adaptation governance, combining doctrinal analysis of EU and international legal frameworks with a bibliometric analysis of the scientific literature. The bibliometric component maps research trends and thematic gaps on gender-responsive climate adaptation. The doctrinal analysis focuses on the European Climate Law, the EU Gender Equality Strategies and selected national instruments, with Spain’s 2021–2030 PNIEC and PNACC as illustrative case studies. These frameworks are assessed against five human-rights-based criteria: substantive equality and intersectionality, participation and empowerment, accountability and access to justice, data and monitoring, and financing and institutional arrangements. The findings reveal a structural “transformation deficit” between normative commitments and operational reality: core climate instruments lack robust requirements on gender impact assessments, sex-disaggregated data, women’s participation and gender-responsive budgeting. The study argues that a truly transformative Gender-Responsive Climate Adaptation (GRCA) in the EU requires moving beyond symbolic references toward binding gender-responsive governance mechanisms derived from CEDAW and EU primary law, capable of dismantling structural barriers and ensuring an environmentally effective and substantively just transition. Full article

In recent years, increasing attention has been paid to the influence of climate change on the distribution and spread of invasive species. However, projections of the future distributions of invasive Ipomoea species remain limited, despite their strong reproductive capacity, ecological adaptability, and competitive ability. In this study, 34 environmental variables were initially considered, and highly correlated variables were removed before fitting Maximum Entropy (MaxEnt) models, with model settings selected according to species-specific sample sizes, to predict the potential distributions of five invasive Ipomoea species (Ipomoea nil, Ipomoea purpurea, Ipomoea quamoclit, Ipomoea lacunosa, and Ipomoea alba) across China under current and future climate scenarios (SSP126, SSP370, and SSP585). Model performance and the contributions of environmental variables were evaluated, and changes in suitable areas and distribution centroids were compared among climate scenarios. All five models showed high predictive performance, with AUC values exceeding 0.9. Snow cover days (SCD) was the main predictor for I. nil and I. purpurea, while Bio9, elevation, and Bio11 were the dominant predictors for I. quamoclit, I. lacunosa, and I. alba, respectively. Compared with the baseline climate period (1981–2010), suitable areas for all five species were projected to expand under future climate scenarios, with varying shifts in distribution centroids. These results indicate that climate warming may increase the potential invasion risk and ecological impacts of invasive Ipomoea species in China, highlighting the need for strengthened monitoring and management to support biodiversity conservation. Full article

During cornering braking, longitudinal braking and lateral tire forces share the limited tire–road adhesion capacity and induce dynamic load transfer among the four wheels, thereby intensifying the coupling between braking performance and lateral stability. Improper braking-force distribution may consequently cause premature tire-force saturation, excessive yaw response, and vehicle sideslip. To address this problem, this study proposes a coordinated cornering-braking stability control strategy for brake-by-wire vehicles. The total braking force is first determined according to the desired deceleration and initially distributed among the four wheels based on their estimated dynamic vertical loads. An improved sliding mode controller with adaptive yaw–sideslip weighting then generates an additional yaw moment, while a sequential quadratic programming algorithm redistributes the wheel braking forces, subject to the total braking-force, additional yaw-moment, and tire-friction-circle constraints. The proposed strategy was evaluated using CarSim/Simulink co-simulations under eight operating conditions involving different initial speeds, braking demands, and road-adhesion levels. Compared with the proportional distribution strategy, the optimized strategy reduced the yaw rate root-mean-square error by 76.2–98.6%, the maximum sideslip angle tracking error by 8.1–97.4%, and the maximum magnitude of the actual sideslip angle by 20.9–98.6%. The improvements were particularly pronounced under high-speed and high-braking-demand conditions. Although the stability-priority allocation moderately extended the braking duration in some cases, it effectively suppressed excessive yaw and sideslip responses, demonstrating its simulation-level effectiveness in improving the cornering-braking stability of brake-by-wire vehicles. Full article

Engineering curricula offer students few structured opportunities to practice reasoning about problems whose social, political, and economic dimensions are as consequential as their technical ones. This paper reports an exploratory qualitative study of an undergraduate engineering elective in which students investigate a wicked problem of their choice using multiple systems mapping tools, with an explicit emphasis on problem exploration over solution convergence. Drawing on semi-structured post-course interviews with 13 purposively sampled students across three cohorts, including a case-based transfer task set in an unfamiliar sociotechnical context, we examine what capacities students describe developing and how specific mapping tools mediate their reasoning. Interviews were analysed through a combined deductive–inductive coding approach organized by the STOP (Systems Thinking for Opportunity) framework, an analytic scaffold that links Richmond’s systems thinking competencies, the KEEN entrepreneurial mindset dimensions, and Ardichvili et al.’s opportunity identification model. Students described a shift from solution-first thinking toward systemic inquiry, characterized mapping tools as scaffolds that externalized assumptions and structured prior knowledge, and displayed reasoning patterns consistent with adaptive transfer in the case task. These capacities did not develop uniformly: students’ accounts foregrounded structural and causal reasoning far more than reasoning about system behaviour over time, opportunity identification rarely progressed into formal opportunity development, and students were candid about where individual tools constrained their analyses. We therefore interpret systems mapping pedagogy as an amplifier of opportunity-relevant cognition rather than a direct producer of entrepreneurial outcomes. Reflecting the purposive, high-performing sample and the interview-based design, findings are offered as exploratory and bounded to this course context. The study contributes a transparent, tool-level account of how mapping practice mediates sociotechnical reasoning, a case-based transfer task with explicit criteria as a model for assessing sociotechnical learning, and design guidance for educators seeking to build sociotechnical capacity in engineering curricula. Full article

Emission reduction remains the foundation of air-pollution control, yet the relationship between reduced emissions and improved ambient air quality is frequently non-proportional. This mismatch is not an exception to atmospheric behavior but a consequence of coupled chemical, meteorological, transport, and removal processes. Here, we critically synthesize global evidence for nonlinear air-quality responses to emission controls, with particular attention to fine particulate matter (PM_2.5) and ozone (O₃). We distinguish five response forms that are directly relevant to policy: near-linear, sublinear, superlinear, threshold, and sign-reversal behavior. Ozone provides the clearest example because the response to nitrogen oxides (NOx) and volatile organic compounds (VOCs) depends on the prevailing photochemical regime and can change as emissions decline. PM_2.5 responses are likewise nonlinear because precursor controls alter atmospheric oxidation capacity, gas-particle partitioning, aerosol water, and interactions among nitrate, sulfate, ammonium, and secondary organic aerosol. Aerosol reductions can further modify photolysis and boundary-layer processes, linking PM_2.5 control to O₃ production. Regional transport and background concentrations attenuate or redistribute the benefits of local controls, while meteorological variability changes both chemical sensitivity and the realized concentration response. These mechanisms imply that sustainable air-quality management cannot be evaluated solely by tonnes of emissions avoided. Instead, policy performance should be assessed along the complete pathway from emission reduction to ambient concentration, exposure, health, climate, ecosystem, equity, and economic outcomes. We propose a sustainability-oriented framework in which control strategies are evaluated for atmospheric effectiveness, multipollutant coherence, spatial equity, climate compatibility, and robustness across changing chemical and meteorological regimes. The evidence supports adaptive, coordinated, and regionally integrated control portfolios rather than fixed single-pollutant reduction ratios. Full article

Simulation studies of surplus electricity in sugarcane cogeneration almost universally assume stable nominal operation, and the sector literature qualitatively acknowledges that many surplus projects underperform; however, this discrepancy has not been systematically quantified against multiyear operational records. Using daily records from seven harvest seasons (2010–2016; 931 valid days) of a Cuban low-pressure sugar mill and the previously published simulation of its own thermal scheme (Termoazúcar STA 4.1), this study quantifies the discrepancy through the Energy Performance Gap (EPG) framework adapted from building science. The export shortfall relative to the simulated baseline ranged from 19.0% to 49.3% per harvest (38.1% aggregated over 2010–2015; 12,835 MWh unrealized) and reached 28.9% for the five-mill provincial aggregate. The gap does not arise from idle capacity—availability is 0.98–1.00, and industrial demand matches the simulated value—but from conversion, with a cane-weighted generation deficit of 5.46 kWh/t ($-12.7$%). Plant steam records proved to be accounting allocations based on fixed coefficients and cannot support correlation-based inference; what they document independently is a contiguous start-of-season regime with pressure-reducing valves in service (39 days of a single harvest), during which specific generation was 11.9 kWh/t lower at statistically identical milling rates (26.15 vs. 38.06 kWh/t; $p<0.001$). No interannual trend was detected (Mann–Kendall, $p=0.368$), although statistical power is limited, at $n=7$. A Monte Carlo characterization of the parametric uncertainty of the simulated baseline (boiler efficiency $\pm 3$%, turbine isentropic efficiency $\pm 5$%, and bagasse moisture $\pm 2$ percentage points) shows that the existence of the gap is robust—the probability of no gap is, at most, 1.1%, even under worst-case uniform perturbations—while widening the intensity-level discount interval to [0.57; 0.93]; a start-of-season depression in specific generation recurs in four of the six estimable harvests, of which the 2015 reducer regime is the most severe instance. As case-specific correction tools, operational discount factors of 0.71 (95% block-bootstrap CI [0.68; 0.75]) for export intensity and 0.62 for total seasonal energy are derived; the underlying procedure, rather than the numerical values, is proposed as transferable. Full article

To enhance renewable energy accommodation and operational flexibility under high renewable energy penetration, this study proposes a multi-objective optimal capacity configuration method for an electricity–heat–hydrogen integrated energy system incorporating a reversible solid oxide cell (RSOC). First, considering the bidirectional electricity–hydrogen conversion capability and waste heat recovery of the RSOC, an electricity–heat–hydrogen multi-energy complementary system is constructed, and efficiency correction models are established for key energy conversion devices to characterize their part-load characteristics. Second, representative source–load scenarios are generated using Latin hypercube sampling and K-means clustering, and a multi-objective optimal capacity configuration model is formulated to minimize the annualized total cost and the wind and photovoltaic power curtailment rate. Finally, given the limitations of the non-dominated sorting genetic algorithm II (NSGA-II) in complex capacity configuration problems, such as premature convergence to local optima and insufficient population diversity, an adaptive crossover and mutation mechanism, a local search strategy, and a dynamic selection mechanism based on comprehensive crowding distance are introduced to improve its optimization performance. A balanced configuration scheme is then selected based on the knee point of the Pareto front obtained by the algorithm. Case-study results show that the Pareto solution set obtained by the improved NSGA-II (INSGA-II) has better overall quality than those obtained by NSGA-II and multi-objective particle swarm optimization (MOPSO). The resulting balanced configuration scheme has an annualized total cost of CNY 422.9 million and a wind and photovoltaic curtailment rate of 2.797%. The proposed method effectively coordinates system economic performance and renewable energy accommodation, enhances the coordinated utilization of electricity, heat, and hydrogen energy flows, and provides a reference for capacity planning of integrated energy systems under high renewable energy penetration. Full article

Riverbank erosion threatens settlements, infrastructure, and river-dependent livelihoods along the Bassac River in the Vietnamese Mekong Delta. This study examines long-term bankline change from 2001 to 2025 and develops expert-informed priorities for assessing livelihood vulnerability within the Can Tho reach. Six Landsat images were analysed in QGIS using the Linear Regression Rate method, while present-day hydraulic conditions were investigated through Acoustic Doppler Current Profiler measurements at five representative locations. An Analytic Hierarchy Process based on interviews with 10 experts was used to derive relative weights for livelihood sensitivity and adaptive-capacity indicators and variables. Accretion was more spatially extensive than erosion along both banks; however, the left bank experienced a greater total extent and magnitude of erosion. Spatially extensive erosion was identified in Binh Thuy, whereas more intense but localised hotspots occurred near Cai Rang and Cai Von. The exploratory hydraulic observations varied among the five selected locations but showed no consistent correspondence with historical erosion magnitude and are therefore interpreted only as a snapshot of conditions on the survey date. Experts assigned weights of 0.547 to sensitivity and 0.453 to adaptive capacity. Savings capacity, decreased food production, extent of land loss, and the ability to shift livelihoods were among the highest-ranked variables. The physical and expert-derived findings support a differentiated and staged approach to riverbank-risk management, but they should be interpreted as complementary evidence rather than as a household-level vulnerability assessment. Future research should combine repeated seasonal hydraulic and bathymetric surveys, bank-material investigations, exposed-asset mapping, and household-based vulnerability assessments. Full article

Historic commercial buildings are often described as resilient, but the mechanisms that sustain ordinary use remain fragmented across morphology, adaptive reuse, heritage governance, and community research. This Review examines how inherited spatial configurations and actor arrangements jointly shape everyday-use resilience. Using transparent, PRISMA-informed searching, screening, appraisal, and narrative/thematic synthesis, we identified 50 eligible empirical studies from 3314 records. Evidence came from 18 countries or regional settings but remained concentrated in Malaysia (9 studies), Indonesia (8), Türkiye (7), and mainland China (7); no eligible study came from the Americas, and direct African evidence was limited to one Egyptian case. In response to prescreen-sensitivity concerns, all 80 records excluded solely because the deterministic dictionary did not detect a spatial-focus term were independently reassessed; 30 were advanced beyond title/metadata review and 13 ultimately met all eligibility criteria. Four evidence-informed spatial capacities recurred: network permeability, fine-grained and reversible subdivision, climatic and service compatibility, and active public–private interfaces. These capacities did not determine resilience independently. Owners and traders translated capacity into maintenance and incremental adaptation; users sustained social legitimacy; and public, professional, financial, and digital intermediaries enabled or constrained adaptation through regulation, investment, programming, and visibility. Heritage retention was assessed in all 50 studies; use vitality was observed in 40 and assessed prospectively in 10; community benefit was observed or partly assessed in 37, prospectively in 10, and not assessed in 3. The geographically concentrated, English-language, public-API, and full-text corpus limits transferability, while the targeted validation demonstrates why deterministic terminology rules require human sensitivity checks. Everyday-use resilience is therefore presented as an evidence-informed, actor-mediated proposition concerning the conversion of inherited spatial capacity into heritage retention, use vitality, and community benefit. Full article

The root phenotype of cotton seedlings serves as a criterion for selecting high-vigour varieties, yet systematic evaluations of Upland Cotton germplasm resources remain limited. We measured nine root- and shoot-related traits in 204 Gossypium hirsutum accessions from diverse ecological regions. Correlation analysis revealed that root surface area, volume, and fresh weight were closely interrelated indicators. Principal component analysis extracted two biologically meaningful factors—‘absorptive capacity’ and ‘morphological strategy’—with a cumulative contribution of 55.72%. Cluster analysis classified the accessions into three functional groups: high-yield potential (n = 15), balanced adaptation (n = 135), and fine-root dominance (n = 54). These clusters corresponded with ecological origins and breeding periods, reflecting local adaptation. We propose root surface area, volume, and fresh weight as cost-effective screening indicators and identified 15 elite accessions as potential parents for root-centred breeding. These findings are particularly relevant for the arid production environments of Northwestern China. Full article

Adaptive reuse is increasingly central to the conservation and enhancement of twentieth-century architectural heritage, where contemporary functions and regulatory requirements must be reconciled with architectural and cultural values. This study investigates how these demands are reconciled in four buildings of different scales, spatial configurations, and original functions within the UNESCO World Heritage site “Ivrea, Industrial City of the 20th Century”. A qualitative multiple-case study was carried out through archival and bibliographic research, architectural drawings, technical documentation, direct observation, and interviews. For each case study, the original configuration (T0) was systematically compared with the post-reuse current configuration (T1). The resulting transformations were assessed through a common interdisciplinary framework comprising eight indicators related to spatial and functional adaptability, social and urban impacts, heritage integrity and conservation, and environmental and technological performance. The cross-case analysis identified recurring strategies and context-specific differences in the adaptive reuse process. The findings suggest that continued use of contemporary heritage buildings depends not only on the preservation of their material fabric, but also on the capacity of reuse interventions to accommodate new or renewed programs without undermining the buildings’ spatial structure, constructional logic, architectural identity, and relationship with their wider urban context. The study therefore conceptualizes cultural continuity as a multidimensional condition encompassing material, spatial, functional, social, and territorial dimensions, and provides an operational framework for critically evaluating adaptive reuse interventions in modern architectural heritage. Full article

Remaining useful life (RUL) prediction of wind-turbine bearings is challenged by nonstationary wind loads, multistage degradation, substantial lifetime dispersion, and strict deployment constraints. Conventional single-task regressors apply a unified feature-to-RUL mapping over the entire life cycle and therefore struggle to characterize stage transitions and bearing-specific degradation progress. To address these issues, this paper proposes a stage-aware multi-task RUL prediction method with causal degradation-prior fusion and collaborative distillation. During training, a high-capacity reference representation path transfers inter-sample relational structures and task-level degradation knowledge to a compact feature encoding path, while only the compact path is retained for inference. Based on the compact representation, a multi-task module jointly performs four-stage classification, stage-conditioned RUL regression, and continuous remaining-life estimation; predicted stage probabilities softly fuse the stage-conditioned outputs. A causal prior-fusion module further integrates a bearing-specific healthy-state anchor, causally identified first prediction time, cumulative damage, and the stage-aware prediction to adapt the RUL trajectory to individual degradation processes. Experiments on the IEEE PHM 2012 and XJTU-SY datasets demonstrate that the proposed method provides accurate and robust RUL prediction across different bearing degradation processes. Moreover, the compact inference path maintains efficient implementation, supporting its potential use in practical wind-turbine condition-monitoring applications. Full article

Escalating track deterioration poses a significant challenge for infrastructure managers seeking to balance increasing capacity demands with long-term sustainability objectives. Although traffic loading is the primary driver of deterioration, existing deterioration models consider a wide range of additional factors whose representation varies across track forms. A comprehensive understanding of these factors is therefore necessary to support informed selection of railway track solutions. This study establishes a conceptual framework of deterioration factors for three railway track solutions: ballasted track, ballastless track, and combined track solutions (CTS). A systematic review of 30 deterioration models was conducted to identify deterioration factors and the mechanisms governing track degradation. Beyond synthesizing factors reported in existing deterioration models, the review identified five additional deterioration factors consistently associated with deterioration mechanisms in the broader railway engineering literature but not explicitly represented in the reviewed models. The review then evaluated the identified factors, grouped them by primary deterioration causes, and adapted them to reflect CTS-specific boundary conditions. The review revealed that existing deterioration models insufficiently address factors related to (i) properties of track subsystems and components, (ii) design characteristics of track forms, and (iii) design, location, and quantity of track transitions. Furthermore, deterioration-related parameters such as the elastic modulus of the track support and the amplitude and wavelength of differential settlement require specific consideration when assessing track form suitability within CTS. The resulting framework provides a structured conceptual representation of deterioration factors and their interrelationships, supporting future development of deterioration prediction models, life cycle cost assessments, and sustainability-oriented decision support methodologies for railway infrastructure. Full article